I'm sure there's probably a simple solution but anyway the problem is this: I've got two classes, say A and B, both of which have attributes that are dataframe like -- those attributes are instances of a dataframe class, call it C, which has its own methods. I'd like to define an 'interface like' class D which has methods that can operate on those attributes (i.e. operate on the dataframes which are attributes of A and B).
edit for clarity: in what follows below, let a and b be dataframes (i.e. instances) from class C. So that the methods of C are available to a and b.
To be more explicit: Suppose a is the dataframe like attribute of A, with attributes Series1,...,Seriesn. Since a is dataframe like, I can call
a.Series1, a.Series2, ... etc to access the contents of Series1, Series2 in a. Of course a is an attribute of A so I'm actually calling A.a.Series1, A.a.Series2.. etc, and a has its own methods from class C so I can call A.a.Series1.methodfromclassC() no problem. Anyhow. Now suppose I want to make a transformation in a consistent fashion to the contents of a.Seriesj, or b.Seriesj, implemented as a method in class D, that both A and B can access. The idea being that I'd like to be able to call a member of class A like so: A.a.Seriesj.transformseries(). The problem I run into is that Seriesj has its own methods (inherited from class C) and transformseries() is not one of them.
This probably seems a bit convoluted but the idea being that eventually I can chain multiple calls to the various methods of D changing the state of the dataframe attributes: A.a.Series2.transform1().transform2().transformj() or B.b.Seriesj.transform6().transform3()
etc, so that the final representation of A.a and B.b is in the form that I'd like.
selfto obtain that kind of thing.ainherits fromCit doesn't necessarily follow thata.Series1inherits fromCas well. Did you think it should, or is part of the explanation missing?ainherits from C anda.Series1inherits from C as well. I'll edit the post for clarity. Thanks